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107	107	**Level**: advanced(%%) **Type**: interactive tutorial
108	108
109	109	Our goal is to implement a new voltage-gated macroscopic current whose properties are described by HH-style equations.
110		-=== [[Using the Channel Builder – Creating a channel from a kinetic scheme specification>>https://neuron.yale.edu/neuron/static/docs/chanlbild/kinetic/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
111	111
112		-**Level**: advanced(%%) **Type**: interactive tutorial
113		-
114		-Here we will implement a new voltage-gated macroscopic current whose properties are described by a family of chemical reactions.
115		-=== [[Randomness in NEURON models– Source code that demonstrates the solution>>https://neuron.yale.edu/neuron/docs/source-code-demonstrates-solution||rel=" noopener noreferrer" target="_blank"]] ===
116		-
117		-**Level**: advanced(%%) **Type**: user documentation
118		-
119		-=== [[Using the Network Builder – Introduction to Network Construction>>https://neuron.yale.edu/neuron/static/docs/netbuild/intro.html||rel=" noopener noreferrer" target="_blank"]] ===
120		-
121		-**Level**: advanced(%%) **Type**: user documentation
122		-
123		-=== [[Python introduction>>https://neuron.yale.edu/neuron/docs/python-introduction||rel=" noopener noreferrer" target="_blank"]] ===
124		-
125		-**Level**: advanced(%%) **Type**: user documentation
126		-
127		-This page provides a brief introduction to Python syntax, Variables, Lists and Dicts, For loops and iterators, Functions, Classes, Importing modules, Writing and reading files with Pickling.
128		-=== [[Reaction-Diffusion Example – RxD with MOD files>>https://neuron.yale.edu/neuron/docs/rxd-mod-files||rel=" noopener noreferrer" target="_blank"]] ===
129		-
130		-**Level**: advanced(%%) **Type**: user documentation
131		-
132		-NEURON's reaction-diffusion infrastructure can be used to readily allow intracellular concentrations to respond to currents generated in MOD files. This example shows you a simple model with just a single point soma, of length and diameter 10 microns, with Hodgkin-Huxley kinetics, and dynamic sodium (declared using rxd but without any additional kinetics).
133		-=== [[Segmenting a simulation of a model network - Introduction>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-network||rel=" noopener noreferrer" target="_blank"]] ===
134		-
135		-**Level**: advanced(%%) **Type**: user documentation
136		-
137		-=== [[Using the Network Builder – Tutorial 1: Making Networks of Artificial Neurons>>https://neuron.yale.edu/neuron/static/docs/netbuild/artnet/outline.html||rel=" noopener noreferrer" target="_blank"]] ===
138		-
139		-**Level**: advanced(%%) **Type**: interactive tutorial
140		-
141		-Learn how to Artificial Integrate and Fire cell with a synapse that is driven by an afferent burst of spikes.
142		-=== [[Reaction-Diffusion Example – Restricting a reaction to part of a region>>https://neuron.yale.edu/neuron/docs/example-restricting-reaction-part-region||rel=" noopener noreferrer" target="_blank"]] ===
143		-
144		-**Level**: advanced(%%) **Type**: user documentation
145		-
146		-Implementation example for the restriction of the reaction to part of a region.
147		-=== [[Segmenting a simulation of a model cell - Introduction>>https://neuron.yale.edu/neuron/docs/segmenting-simulation-model-cell||rel=" noopener noreferrer" target="_blank"]] ===
148		-
149		-**Level**: advanced(%%) **Type**: user documentation
150		-
151		-=== [[Scripting NEURON basics>>https://neuron.yale.edu/neuron/docs/scripting-neuron-basics||rel=" noopener noreferrer" target="_blank"]] ===
152		-
153		-**Level**: advanced(%%) **Type**: user documentation
154		-
155		-The objectives of this part of the tutorial are to get familiar with basic operations of NEURON using Python. In this worksheet we will: Create a passive cell membrane in NEURON. Create a synaptic stimulus onto the neuron. Modify parameters of the membrane and stimulus. Visualize results with bokeh.
156		-